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October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.
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International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.
October 5, 2026
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Linara Khadimullina works in the field of low-carbon development. In an interview with the Young Scientists of HSE project, she spoke about why nature is not just a beautiful backdrop, her research on the role of sustainable corporate governance in reducing greenhouse gas emissions, and growing plants as a source of inspiration.

 

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Dynamics in the Predictability of Credit Default Swap Spreads of EU Companies

Complexity. 2023. Vol. 2023. Article 7572061.
Kirill Romanyuk, Sarvar Anvarov, Mark Shumilov, Alecksey Zheleyko

The COVID-19 pandemic affected financial instruments and markets all around the world. Credit default swap contracts of EU companies were analysed in this paper. The data consist of daily credit default swap spreads and market capitalisations of EU companies, exchange rates, LIBOR rates, bond yields, and commodity futures prices from January 2010 to February 2022. The dynamics in the performance of forecasting models for credit default swap spreads before and after the declaration of the COVID-19 pandemic were measured by relative error metrics, i.e., relative root mean squared error, relative mean absolute error, and relative mean absolute percentage error. The results show a small drop in the performance right after the declaration of the COVID-19 pandemic that is mitigated by strong performance in the rest of the year, followed by a significant drop in the performance in the second year of the pandemic.

Research target: Economics and Management
Language: English
DOI
Text on another site
Keywords: Credit default swapsкредитные дефолтные свопыпредсказуемостьpredictabilityCOVID-19COVID-19
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